Wireless communication systems have become increasingly prevalent in today's society. Such systems enable mobile users to travel freely within the service area of the network and communicate via a wireless communication device with telephones, facsimile devices, computers, e-mail subscribers, other wireless communication devices and any of a number of other computer-based devices that support wireless communication.
The current landscape of wireless communication includes a multitude of wireless communication services based on different technologies and offering different features to mobile users. For instance, analog advanced mobile phone services (AMPS), which were implemented in the 1980's, provide basic calling and voice mail. Digital advanced mobile phone service (D-AMPS) provide advanced features such as caller identification and paging. D-AMPS uses multiplexing techniques such as time division multiple access (TDMA) and code division multiple access (CDMA) to give wireless carriers more capacity on existing channels. Other services, such as global system for mobile communications (GSM) and personal communications service (PCS), offer similar features. More advanced wireless communication services, such as cellular digital packet data (CDPD), specialized mobile radio (SMR), wideband CDMA (WCDMA), general packet radio service (GPRS), services based on wireless access protocol (WAP), Internet protocol (IP), file transfer protocol (FTP), hyper text transfer protocol (HTTP) and other known data communication protocols, and other “second generation” (2G) and “third generation” (3G) services provide numerous types of wireless data communication services. For example, these advanced wireless data communication services enable mobile users to access data from numerous sources via public or private packet-switched or other data networks including the Internet, circuit switched networks such as the public switched telephone network, or other wireless networks.
The complex mixture of different wireless communication technologies and different wireless devices makes evaluating the data performance of data networks a very difficult task. Measuring the data service quality, as opposed to voice quality, of a wireless network is particularly problematic. For instance, when transmitting voice over a wireless network, the wireless network may still support voice in areas within a cell, such as within buildings or where terrain or other factors are a problem, where the signal to noise ratio is limiting. In order to continue voice service, the wireless network reduces the information capacity of the voice signal so that it may still be carried over the voice channel. In such instances, although there may be reduced voice quality, the mobile user may still be able to discern what is being said. However, when transmitting raw data over a wireless network, reducing the information capacity of the data signal to accommodate areas with a poor signal to noise ratio effects the content of the data being transmitted. Thus, there are many locations within a wireless data network where voice service may be provided adequately, but where the quality of data service would be unacceptable to mobile users.
One current approach to approximating the quality of data service in a wireless data network involves using simulation and planning techniques. This approach is very problematic because it is not based on actual network measurements, but instead relies on theoretical assumptions about how engineering parameters actually relate to the quality of data service as perceived by mobile users. This approximation also does not take into account non-predictive measurements such as call setup times and server delays or errors that also decrease the user's perceived quality of service.
Another current approach to measuring the quality of data service in a wireless data network involves manually initiating data calls using standard modem utilities at discrete positions within a wireless data network and measuring the quality of data service at each position. However, this approach is very problematic. In order to develop an effective “data footprint” of a wireless data network, thousands of individual tests must be run. Furthermore, separate tests and measurements must be run for each wireless data network being tested and the locations of the tests need to be individually hand mapped with the collected data. The data collected by this approach is usually input into a spreadsheet for additional analysis, which may introduce errors in the measurements. This manual approach is very time-consuming and consequently very costly.
Thus, a heretofore unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.